This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH ₄ ) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH ₄ flux measurements globally, initial results comparing CH ₄ fluxes across the sites, and future research directions and needs. Annual estimates of net CH ₄ fluxes across sites ranged from −0.2 ± 0.02 g C m ^–2 yr ^–1 for an upland forest site to 114.9 ± 13.4 g C m ^–2 yr ^–1 for an estuarine freshwater marsh, with fluxes exceeding 40 g C m ^–2 yr ^–1 at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH ₄ flux across wetland sites globally. Water table position was positively correlated with annual CH ₄ emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH ₄ fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH ₄ estimates due to gap-filling and random errors were on average ±1.6 g C m ^–2 yr ^–1 at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH ₄ flux database, the controls on ecosystem CH ₄ fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH ₄ emissions.

Methane (CH₄) emissions from natural landscapes constitute roughly half of global CH₄ contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH₄ flux are ideal for constraining ecosystem-scale CH₄ emissions due to quasi-continuous and high-temporal-resolution CH₄ flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH₄ Version 1.0, the first open-source global dataset of CH₄ EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH₄ includes half-hourly and daily gap-filled and non-gap-filled aggregated CH₄ fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH₄ representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH₄ Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH₄ emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH₄ fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH₄ emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20^∘ S to 20^∘ N) the spring onset of elevated CH₄ emissions starts 3 d earlier, and the CH₄ emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH₄ emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH₄ emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH₄ emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH₄ emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH₄ modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH₄ peak). FLUXNET-CH₄ is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH₄ cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH₄ data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

Wetland methane (CH₄) emissions ( $${F}_{{{CH}}_{4}}$$F C H 4 ) are important in global carbon budgets and climate change assessments. Currently, $${F}_{{{CH}}_{4}}$$F C H 4 projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent $${F}_{{{CH}}_{4}}$$F C H 4 temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that $${F}_{{{CH}}_{4}}$$F C H 4 are often controlled by factors beyond temperature. Here, we evaluate the relationship between $${F}_{{{CH}}_{4}}$$F C H 4 and temperature using observations from the FLUXNET-CH₄ database. Measurements collected across the globe show substantial seasonal hysteresis between $${F}_{{{CH}}_{4}}$$F C H 4 and temperature, suggesting larger $${F}_{{{CH}}_{4}}$$F C H 4 sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH₄ production are thus needed to improve global CH₄ budget assessments.

We mapped tidal wetland gross primary production (GPP) with unprecedented detail for multiple wetland types across the continental United States (CONUS) at 16‐day intervals for the years 2000–2019. To accomplish this task, we developed the spatially explicit Blue Carbon (BC) model, which combined tidal wetland cover and field‐based eddy covariance tower data into a single Bayesian framework, and used a super computer network and remote sensing imagery (Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index). We found a strong fit between the BC model and eddy covariance data from 10 different towers (r² = 0.83, p < 0.001, root‐mean‐square error = 1.22 g C/m²/day, average error was 7% with a mean bias of nearly zero). When compared with NASA's MOD17 GPP product, which uses a generalized terrestrial algorithm, the BC model reduced error by approximately half (MOD17 had r² = 0.45, p < 0.001, root‐mean‐square error of 3.38 g C/m²/day, average error of 15%). The BC model also included mixed pixels in areas not covered by MOD17, which comprised approximately 16.8% of CONUS tidal wetland GPP. Results showed that across CONUS between 2000 and 2019, the average daily GPP per m² was 4.32 ± 2.45 g C/m²/day. The total annual GPP for the CONUS was 39.65 ± 0.89 Tg C/year. GPP for the Gulf Coast was nearly double that of the Atlantic and Pacific Coasts combined. Louisiana alone accounted for 15.78 ± 0.75 Tg C/year, with its Atchafalaya/Vermillion Bay basin at 4.72 ± 0.14 Tg C/year. The BC model provides a robust platform for integrating data from disparate sources and exploring regional trends in GPP across tidal wetlands.

In the southwest United States, the current prolonged warm drought is similar to the predicted future climate change scenarios for the region. This study aimed to determine patterns in vegetation response to the early 21st century drought across multiple biomes. We hypothesized that different biomes (forests, shrublands, and grasslands) would have different relative sensitivities to both climate drivers (precipitation and temperature) and legacy effects (previous‐year's productivity). We tested this hypothesis at eight Ameriflux sites in various Southwest biomes using NASA Moderate‐resolution Imaging Spectroradiometer Enhanced Vegetation Index (EVI) from 2001 to 2013. All sites experienced prolonged dry conditions during the study period. The impact of combined precipitation and temperature on Southwest ecosystems at both annual and sub‐annual timescales was tested using Standardized Precipitation Evapotranspiration Index (SPEI). All biomes studied had critical sub‐annual climate periods during which precipitation and temperature influenced production. In forests, annual peak greenness (EVI_max) was best predicted by 9‐month SPEI calculated in July (i.e., January–July). In shrublands and grasslands, EVI_max was best predicted by SPEI in July through September, with little effect of the previous year's EVI_max. Daily gross ecosystem production (GEP) derived from flux tower data yielded further insights into the complex interplay between precipitation and temperature. In forests, GEP was driven by cool‐season precipitation and constrained by warm‐season maximum temperature. GEP in both shrublands and grasslands was driven by summer precipitation and constrained by high daily summer maximum temperatures. In grasslands, there was a negative relationship between temperature and GEP in July, but no relationship in August and September. Consideration of sub‐annual climate conditions and the inclusion of the effect of temperature on the water balance allowed us to generalize the functional responses of vegetation to predicted future climate conditions. We conclude that across biomes, drought conditions during critical sub‐annual climate periods could have a strong negative impact on vegetation production in the southwestern United States.

The exchange of carbon between the Earth’s atmosphere and biosphere influences the atmospheric abundances of carbon dioxide (CO₂) and methane (CH₄). Airborne eddy covariance (EC) can quantify surface-atmosphere exchange from landscape-to-regional scales, offering a unique perspective on carbon cycle dynamics. We use extensive airborne measurements to quantify fluxes of sensible heat, latent heat, CO₂, and CH₄ across multiple ecosystems in the Mid-Atlantic region during September 2016 and May 2017. In conjunction with footprint analysis and land cover information, we use the airborne dataset to explore the effects of landscape heterogeneity on measured fluxes. Our results demonstrate large variability in CO₂ uptake over mixed agricultural and forested sites, with fluxes ranging from −3.4 ± 0.7 to −11.5 ± 1.6 μmol m⁻² s⁻¹ for croplands and −9.1 ± 1.5 to −22.7 ± 3.2 μmol m⁻² s⁻¹ for forests. We also report substantial CH₄ emissions of 32.3 ± 17.0 to 76.1 ± 29.4 nmol m⁻² s⁻¹ from a brackish herbaceous wetland and 58.4 ± 12.0 to 181.2 ± 36.8 nmol m⁻² s⁻¹ from a freshwater forested wetland. Comparison of ecosystem-specific aircraft observations with measurements from EC flux towers along the flight path demonstrate that towers capture ∼30%–75% of the regional variability in ecosystem fluxes. Diel patterns measured at the tower sites suggest that peak, midday flux measurements from aircraft accurately predict net daily CO₂ exchange. We discuss next steps in applying airborne observations to evaluate bottom-up flux models and improve understanding of the biophysical processes that drive carbon exchange from landscape-to-regional scales.